Software Platform for Analyzing Alzheimer's and Parkinson's fMRI Connectomes
Software Platform for Analyzing Alzheimer's and Parkinson's fMRI Connectomes
批准号:
9139293
负责人:
WILLIAM D. SHANNON
金额:
$55.16万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-05-15 至 2018-04-30
关键词:
AccountingAddressAlgorithm DesignAlgorithmsAlzheimer&aposs DiseaseAreaBRAIN initiativeBiological MarkersBiomedical ResearchBrainBrain DiseasesBrain imagingBrain regionBusinessesCardiovascular DiseasesClinicClinical ResearchClinical SciencesClinical TreatmentComplexComputer softwareContractsDataData AnalysesData AnalyticsDevelopmentDiabetes MellitusDiseaseDrug TargetingElectroencephalographyEnsureExperimental DesignsFeedbackFunctional Magnetic Resonance ImagingFundingFutureGoalsGraphHumanImageryIndustryLicensingLong-Term CareMarketingMeasuresMental HealthMethodsModelingNeurosciencesOnset of illnessOutcomeParkinson DiseasePatientsPatternPerformancePharmaceutical PreparationsPharmacologic SubstancePhasePositron-Emission TomographyPrevalencePrevention ResearchPublishingResearchResearch PersonnelScienceSmall Business Innovation Research GrantSocial WorkSoftware DesignSpeedStatistical AlgorithmStatistical MethodsSubgroupTechnologyTestingTimeTranslational ResearchUnited States National Institutes of HealthUniversitiesWorkbiomarker discoverycloud basedcommercial applicationconnectomecostdisease diagnosisimprovedinnovationmeetingsnovelnovel therapeuticsopen sourceprogramspublic health relevancereal world applicationresearch and developmentsingle photon emission computed tomographysocialsoftware as a servicetooltranslational clinical trialtranslational neuroscienceweb based interface
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): It is estimated that the cost in the US for brain disorders per year is $500 billion for treatment and long term care, with another $400 billion in other nonmedical costs. As a consequence, reducing the burden of human brain disorders is a key focus of the NIH BRAIN Initiative, with one strategy being the use of fMRI connectomes to study brain region functioning. Current approaches for analyzing connectomes use 'off-the-shelf' statistical methods not optimized for this type of data. In this Direct to Phase II SBIR we propose
to further develop and strengthen our graphical object oriented data analysis software to solve data analysis, experimental design, and hypothesis testing problems in translational neuroscience. Product: This SBIR will produce analytical software for fMRI data in translational research. Users will access the software through a cloud-based Software-as-a-Service (SaaS) contract. The technical innovation of this SBIR statistical software designed specifically and optimized for fMRI brain imaging data is to support moving fMRI technology from basic R&D to translational clinical science. The impact of this technology are tools to improve brain imaging experimental design, improve biostatistical analysis of brain imaging data, and ultimately improve discovery of biomarkers and identify possible drug targets for clinical treatment. Long term goal: Extending our cloud-based Software-as-a-Service (SaaS) data analytics platform offers researchers an easy to use web-based interface for analyzing new and complex biomedical research data. As a platform technology, there are many applications in other areas of biomedical research that can be developed. Therefore, our business strategy is to identify the areas of science that have the greatest potential to make the move from the university research setting into the commercial arena, and that produce novel or complex data with no commercial analytics tools for translational clinical trials yet on the market. The Specific Aims of this SBIR
Direct to Phase II project are: Aim 1: Develop statistical algorithms and software. Aim 2: Validate the methods. Aim 3: Apply the methods to real data. Expected outcomes: Validated statistical software proven to be more powerful than existing methods for analyzing fMRI connectome data in translational research.
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批准号:9519378
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财政年份:2016
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依托单位:
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财政年份:2012
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依托单位:
NEW OBSERVATIONAL DATA ANALYSIS METHODS FOR COMPARATIVE EFFECTIVENESS RESEARCH
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资助金额:$150.0万
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财政年份:2010
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依托单位:
NEW DATA ANALYSIS METHODS FOR ACTIGRAPHY IN SLEEP MEDICINE
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依托单位:
NEW DATA ANALYSIS METHODS FOR ACTIGRAPHY IN SLEEP MEDICINE
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财政年份:2009
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负责人:WILLIAM D. SHANNON
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依托单位:
NEW DATA ANALYSIS METHODS FOR ACTIGRAPHY IN SLEEP MEDICINE
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项目类别:
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资助金额:$37.82万
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财政年份:2009
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负责人:WILLIAM D. SHANNON
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依托单位:
STATISTICAL METHODS FOR RECURSIVELY PARTITIONED TREES
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项目类别:
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财政年份:2000
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负责人:WILLIAM D. SHANNON
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依托单位:
STATISTICAL METHODS FOR RECURSIVELY PARTITIONED TREES
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批准号:6387141
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项目类别:
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资助金额:$16.34万
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财政年份:2000
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负责人:WILLIAM D. SHANNON
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依托单位:
STATISTICAL METHODS FOR RECURSIVELY PARTITIONED TREES
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依托单位:
海外基金